In the early 1980s, the emergent computer industry incorporated mathematician and physicists John Von Neumann's distributed theorized compute model. Von Neumann's theories were way ahead of his time and were conceived long before the personal computing era became a reality. The Von Neumann model enabled the notion that many smaller computers could scale and produce higher computer power than a single centralized expensive computer (e.g., mainframe). As the Digital Age began, the personal computer not only became powerful but also grew in presence in homes and offices, bringing the usefulness of applications. Overtime, the personal computer (PC) out grew just being a desktop device and expanded into the data center and morphed into servers. Servers in the data center transformed into the client-server market and the well-known distributed compute model that John Von Neumann theorized forty-five years prior became reality.
For decades the PC, laptops and servers have been known to use RISC, PowerPC, ARM® and x86 architectures for processing power (CPU), limited memory (e.g., Random Access Memory RAM) and Hard Disk (HDA) devices for storage media. As the digital era continued to expand, the content computers created continued to get richer, larger in density and drove yearly innovation and upgrades in computer processing power (CPU), RAM capacities and hard drive densities. There continues to be several detriments to this approach; (1) not all components are gaining performance while gaining density [Moore's Law]; (2) the I/O interfaces of these elements are not the same speed, creating I/O bottlenecks [Kryder's Law].
A well-known upgrade technique in the computer industry has been to upgrade a computers memory (RAM) to get more performance out of a machine. Conversely, memory (RAM) capacities have been limited by several key factors, the CPU processor, nanometer density limitations of silicon, and power dissipation. By today's standards the largest memory module available is only 128 GB in capacity in contrast to the largest computer hard drive is 6 TB in capacity. In this example the hard drive is 93.75× larger than the memory module; this is the density issue. Contrariwise, the maximum input/output (I/O) transfer speed for memory modules (i.e., RAM) is currently 56.7 GB per sec, and the maximum I/O transfer speed for a Serial Attached SCSI (SAS-II) interface is currently 750 MB per sec. Thus, the memory module is 76.8 faster than today's SAS-II hard drive.
Under light computing loads, one might not notice this imbalance or battle of density vs. performance. However under a heavy computing load there is no equalizing this major imbalance of density vs. performance and I/O bottlenecks inevitably will occur. These eventually will slow the entire computing operation to the speed of the hard drive. The futile attempt to avoid this is to add more systems at the problem and rewrite applications to further distribute applications over more processor cores.
The answer to this quintessential problem would be to add more memory (RAM) and write application algorithms to alleviate the bottlenecks.
Nevertheless, the next challenge materializes, cost. Memory (RAM) in general can be very expensive depending of the density of the RAM module. A real world example of how expensive RAM is that the largest available memory module currently available is 64 GB. A single 64 GB RAM module currently sells for about $1,000.00 USD per module. The average x86 server motherboard currently sells for about $700.00 USD and can use up to 16 or 24 RAM modules. By fully populating an inexpensive x86 motherboard with 16 modules currently would cost about $16,000.00 USD; this makes RAM about 20 times more expensive than the inexpensive motherboard and would yield only 1 TB of RAM.
In an unflawed world, computers would need only memory (RAM) and high speed processors. If the challenge of density and cost did not exist, then computers without storage devices would be possible. The hurdle becomes how a memory modules (RAM) functions. All memory modules today are considered a volatile technology, meaning that when you power off a compute system, the memory losses power and the memory becomes erased. Storage device media of today do not have this issue—when the power is removed, storage device media retain the information that had been written to them. When you combine all of the factors of density, performance, cost and volatility, one can quickly deduce the reality of a computer with only CPU and RAM has been unachievable.
What is needed is an improved computing system to overcome the drawbacks the conventional art described above.